Longer term monitoring of soil water content at a catchment scale is a key to understanding its dynamics, which can assist stakeholders in decision making processes, such as land use change or irrigation programs. Soil water monitoring in agriculturally dominated catchments can help in developing soil water retention measurements, for assessment of land use change, or adaptation of specific land management systems to climate change. The present study was carried out in the Pannonian region (Upper-Balaton, Hungary) on Cambisols and Calcisols between 2015 and 2021. Soil water content (SWC) dynamics were investigated under different land use types (vineyard, grassland, and forest) at three depths (15, 40, and 70 cm). The meteorological data show a continuous decrease in cumulative precipitation over time during the study with an average of 26% decrease observed between 2016 and 2020, while average air temperatures were similar for all the studied years. Corresponding to the lower precipitation amounts, a clear decrease in the average SWC was observed at all the land use sites, with 13.4%, 37.7%, and 29.3% lower average SWC for the grassland, forest, and vineyard sites, respectively, from 2016 to 2020 (measured at the 15 cm depth of the soil). Significant differences in SWC were observed between the annual and seasonal numbers within a given land use (p < 0.05). The lowest average SWC was observed at the grassland (11.7%) and the highest at the vineyard (28.3%). The data showed an increasing average soil temperature, with an average 6.3% higher value in 2020 compared to 2016. The grassland showed the highest (11.3 °C) and the forest soil the lowest (9.7 °C) average soil temperatures during the monitoring period. The grassland had the highest number of days with the SWC below the wilting point, while the forest had the highest number of days with the SWC optimal for the plants.
Methods enabling stakeholders to receive information on plant stress in agricultural settings in a timely manner can help mitigate a possible decrease in plant productivity. The present work aims to study the soil–plant interaction using field measurements of plant reflectance, soil water content, and selected soil physical and chemical parameters. Particular emphasis was placed on sloping transects. We further compared ground- and Sentinel-2 satellite-based Normalized Vegetation Index (NDVI) time series data in different land use types. The Photochemical Reflectance Index (PRI) and NDVI were measured concurrently with calculating the fraction of absorbed photochemically active radiation (fAPAR) and leaf area index (LAI) values of three vegetation types (a grassland, three vineyard sites, and a cropland with maize). Each land use site had an upper and a lower study point of a given slope. The NDVI, fAPAR, and LAI averaged values were the lowest for the grassland (0.293, 0.197, and 0.51, respectively), which showed the highest signs of water stress. Maize had the highest NDVI values (0.653) among vegetation types. Slope position affected NDVI, PRI, and fAPAR values significantly for the grassland and cropland (p < 0.05), while the soil water content (SWC) was different for all three vineyard sites (p < 0.05). The strongest connections were observed between soil physical and chemical parameters and NDVI values for the vineyard samples and the selected soil parameters and PRI for the grassland. Measured and satellite-retrieved NDVI values of the different land use types were compared, and strong correlations (r = 0.761) between the methods were found. For the maize, the satellite-based NDVI values were higher, while for the grassland they were slightly lower compared to the field-based measurements. Our study indicated that incorporating Sentinel-derived NDVI can greatly improve the value of field monitoring and provides an opportunity to extend field research in more depth. The present study further highlights the close relations in the soil–plant–water system, and continuous monitoring can greatly help in developing site-specific climate change mitigating methods.
Land use and management affect soil hydrological processes, and the impacts can be further enhanced and accelerated due to climate change. In this study, we analyzed the possible long-term effects of different land use types on soil hydrological processes based on future climatic scenarios. Soil moisture and temperature probes were installed at four land use sites, a cropland, a vineyard, a meadow, and a forest area. Based on modeling of long-term changes in soil water content (SWC) using the HYDRUS 1D model, we found that changes in precipitation have a more pronounced effect on soil water content than changes in air temperature. Cropland is at the highest risk of inland water and SWC values above field capacity (FC). The number of days when the average SWC values are above FC is expected to increase up to 109.5 days/year from the current 52.4 days/year by 2081–2090 for the cropland. Our calculations highlight that the forest soil has the highest number of days per year where the SWC is below the wilting point (99.7 days/year), and based on the worst-case scenario, it can increase up to 224.7 days/year. However, general scenario-based estimates showed that vineyards are the most vulnerable to projected climate change in this area. Our study highlights the limitations of potential land use change for specific agricultural areas, and emphasizes the need to implement water retention measures to keep these agricultural settings sustainable.
The main objective of this study was to investigate soil–plant–water interactions based on field measurements of plant reflectance and soil water content (SWC) in different inter-row managed sloping vineyards. The following three different soil management applications were studied: tilled (T), cover crops (CC), and permanent grass (NT) inter-rows. We measured SWCs within the row and between rows of vines. Each investigated row utilized 7 to 10 measurement points along the slope. Topsoil SWC and temperature, leaf NDVI and chlorophyll concentrations and leaf area index (LAI) were measured every two weeks over the vegetation period (May to November) using handheld instruments. We found that management method and slope position can significantly affect the soil’s physical and chemical properties, such as clay or soil organic carbon contents. Cover crops in the inter-row significantly reduced average SWC. The in-row average topsoil SWCs and temperatures were lower in all study sites compared to the values measured in between rows. Significantly higher SWCs were observed for the upper points compared to the lower ones for CC and T treatments (58.0 and 60.9%, respectively), while the opposite was noted for NT. Grassed inter-row grapevines had significantly lower leaf chlorophyll content than the other inter-row managed sites (p < 0.001). The highest average leaf chlorophyll contents were observed in the T vineyard (16.89 CCI). Based on slope positions, the most distinguishable difference was observed for the CC: 27.7% higher chlorophyll values were observed at the top of the slope compared to the grapevine leaves at the bottom of the slope (p < 0.01). The leaf NDVI values were not as profoundly influenced by slope position in the vineyard as the chlorophyll values were. For overall LAI values, the T treatment had significantly lower values compared to NT and CC (p < 0.001). Moderate correlations were observed between NDVI and LAI and soil nitrogen and carbon content. In general, we found that both inter-row management and slope position can significantly influence soil parameters and affect plant growth, and consequently can accelerate plant stress under sub-optimal environmental conditions such as prolonged drought.
<p>In agricultural systems, rapid information from data collection and processing is an important factor for stakeholders and researchers to correctly account for the spatial and temporal variability of crop and soil factors. The aim of the present study was to investigate soil-plant-water systems and interactions using manual and remote sensing techniques in a small agricultural catchment. Four land use types of forest, grassland, vineyard, and cropland (sunflower) were investigated in different slope positions. At the same time, three different tillage practices were applied in the vineyard between the rows: grassed (NT), cover cropped (CC), and tilled (T) inter rows. We evaluated NDVI measurements from three different sources (PlantPen - PP, Meter Group - MG, Sentinel-2 - S2) representing different scales (leaves, 0.33m<sup>2</sup>, and 100m<sup>2</sup>). We also compared ground and satellite measurements of varying vegetation indices.</p> <p>Spectral reflectance sensors were used on the slopes of grassland, cropland, and three vineyard sites. The Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to measure leaf reflectance. A hemispherical sensor set was used for each measurement. Hand-held instruments were used to measure the topsoil soil water content (SWC) and temperature, leaf NDVI and chlorophyll concentrations, and Leaf Area Index (LAI) every two weeks. Satellite data, such as NDVI, green (GCI) and red edge (RECI) chlorophyll indices, and soil-adjusted vegetation index (SAVI), were obtained from the Sentinel-2 database on days when both ground and satellite overpass occurred within 24 hours.</p> <p>Land use types and slope position have a strong influence on vegetation growth. The highest overall NDVI and leaf chlorophyll values were observed in vineyard and forest samples, and the lowest in grassland. SWC and temperature were the lowest in the forest and vineyards. SWCs were significantly different for T and CC samples (p<0.05) based on slope positions, while soil temperatures were not significantly different between upper and lower slope positions (p>0.05). For the other three land use types, there were no significant differences in values between slope positions. Chlorophyll data showed a very strong correlation between Sentinel-2 retrieved data and hand-held measurements, with r=0.84 for grassland (GCI), r=0.83 for NT (GCI), and r=0.87 for T (RECI). Strong correlations were found between the different sources of NDVI for the grassland samples (e.g. r=0.97, p<0.05 for S2 and MG). Weaker correlations were observed between different inter-row managed vineyard samples (e.g. for tilled inter-row r=0.70 between S2 and PP and r=0.35 between S2 and MG). Since inter-row management strongly influences the overall values of S2, adjustments are needed.</p>
<p>Soil-plant-water monitoring allows stakeholders to obtain rapid information on plant stress caused by water or nutrient deficiencies. The main objective of the study was to investigate soil-plant-water interactions based on field measurements of plant reflectance and soil water content (SWC) under different land use types and inter-row managed vineyards. Four main study sites were investigated during the vegetation period: forest, grassland, cropland (sunflower), and vineyard. Three different soil management applications were studied in the vineyard: tilled (T), cover crops (CC), and grass (NT) inter-rows. SWCs were also measured within the row and between rows of vines to get a more complete picture of the hydrology of the sites. At each study site, we had several measurement points along a slope section, where each slope is prone to erosion. For continuous hydrological monitoring soil water and temperature sensors were placed 15 and 40cm below the ground at the top and bottom of the slopes. Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to measure leaf reflectance. All sites included a set of hemispherical sensor sets. Topsoil SWC, leaf NDVI and chlorophyll concentrations, and Leaf Area Index (LAI) were measured every two weeks using hand-held instruments.</p><p>Among the four land use types, the lowest SWC and soil temperature of the upper 20cm was observed in the forest, and the highest in the cropland. The in-row average topsoil SWCs and temperatures were lower in all study sites compared to the values measured in between rows. The lowest chlorophyll and NDVI values were observed in grassland, which also showed the highest drought stress. The grassed inter-row grapevines had significantly lower leaf chlorophyll contents than the other inter-row managed sites (<em>p</em><0.001). The highest leaf chlorophyll contents were observed in the forest samples (17.14CCI) and the tilled vineyard (16.89CCI). Based on slope positions, the most distinguishable difference was observed for the CC vineyard plants, 17.6% higher values were observed at the top of the slope compared to the leaves at the bottom of the slope (<em>p</em><0.01). The leaf NDVI values were not influenced by slope positions for the vineyard, cropland, or forest. However, significantly higher chlorophyll and NDVI values were noted for the grassland lower points than the upper. The most distinguishable differences between lower and upper slope positions&#8217; SWC values were observed for the tilled vineyard slope, 59.4% and 35.0% higher overall SWC were measured for the in-row and between-row, respectively. Overall LAI values were the highest for the forest and the lowest for the grassland, where slope position did not affect plant leaf areas significantly.&#160;The steadily decreasing annual precipitation amount (from 740mm to 422mm between 2016 and 2022) makes the area more vulnerable to climate change and highlights the need for future work on the applications of water retention measures.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.